Higher: estimating IQR and comparing cumulative distributions
Higher: estimate quartiles and IQR from cumulative-frequency graphs and compare distributions using their own sample totals.
Exam scope and assessment notes
The first four lessons are shared Foundation work inherited by Higher; the last four are additional Higher spread, quartile and cumulative-frequency reading work. Keep the actual repeated observations and frequencies, state units, and distinguish an average from spread. Grouped midpoint means and within-class graph readings are estimates. The chosen discrete quartile rule is median of each half, excluding the overall middle observation when the count is odd; it is not claimed as a universal Pearson algorithm. Draw the horizontal and vertical guides yourself, use each graph’s own total, and retain a full plateau interval when an inverse is not unique. Fixed numerical agreement does not mark reasoning or award marks or mastery. Specialist and formal-assessment approval remain pending. This is the Issue 2 linear 4MA1 scope: November 2026/June 2027 entries and regional-centre eligibility differ from modular awards. Literal second-edition Book2 Handling Data4/5/6 and Hub tags guide navigation only; no Book1 6.2 tag or verified chapter/Hub body is inferred. Handling Data6 map208–222 conflicts with proof chapter207/summary221/next222; Handling Data4 map39–60 extends beyond summary59 before next61. Graphical representation6.1 and probability6.3 remain separate.
Before you begin
- Draw median read-offs on cumulative graphs.
- Calculate quarter and three-quarter fractions.
- Subtract signed or decimal values and interpret intervals.
Work on paper. Try each question before revealing help, and explain why your method works.
Quick readiness check
A complete cumulative graph contains 56 observations. Which two cumulative heights locate its quartiles?
What you will learn
- Locate quartile read-offs at N/4 and 3N/4 on each complete cumulative graph.
- Subtract unrounded value readings to estimate IQR and handle interval-valued quartile readings.
- Compare centre and spread in common units while accounting for different sample sizes.
From the supplied CF guide through (0,0), (10,8), (20,24), (30,36), (40,40), draw quartile read-offs and estimate the IQR to 1 decimal place. Keep unrounded readings until subtraction. On the supplied calibrated diagram, show each requested horizontal and vertical read-off guide; keep the measurement unit and any complete overlap interval.
Enter your own actual observations, positions, products, operations and guide endpoints. No count, total, role, result, quartile, graph height, unit or precision is filled for you. Recording is an attempt, not a correctness result.
Original supplied observations and tables
Only literal observations, frequencies, intervals and supplied cumulative guides are shown initially. The display does not sort observations, compute a total, average, quartile, rank or recovered value, or prefill a learner operation.
All metric panels share one stable camera. Measurement and cumulative-count axes have separately labelled scales; an observation index is not a planar data coordinate. Pan, zoom and whole-view turns change only the frame.
Supplied cumulative guide G1
given: Literal supplied values only.
Supplied cumulative guide G1
given: Supplied values only.
Blue denotes literal supplied guides, amber actual entered work, purple dirty retained work, and green a separately gated reference. Wrong and partial values are never repaired. The drawing bound is±1,000,000 coordinates, with at most512 scalar entries and128 cumulative points; these are tool bounds, not mathematical laws. Native clipping does not clamp values. No completed target is silently substituted.
The selected median-of-halves convention excludes the overall middle observation for odd lists. Grouped means and guide read-offs remain estimates. A zero-frequency plateau can give an interval rather than a unique reading. Fixed guide comparisons use the separate canonical700×500 policy with each source total; the tolerance is not a current-screen pixel or official marking tolerance. Text presence, operation consistency and numerical self-check do not approve reasoning, statistical claims, marks, mastery, teacher/specialist or formal assessment. No probability or new boxplot teaching credit is granted.
G1 Q1: draw horizontal guide, every vertical read-off and any full overlap
No actual work is recorded for this action.
State explicitly whether your reading has an interval overlap.
Only a selected CF endpoint uses the board. The reading bounds, ranks, list positions and operation rows are separate scalar work. Add each vertical leg yourself; a second leg or overlap is never invented.
My quantities, conclusions and explanation
For a numerical list, use comma-separated values with no brackets or one balanced enclosing pair, or type none when you mean no mode. State the actual unit and exact, estimate or one-decimal-place precision yourself.
Retain the stated data, units, signs and precision. Numerical agreement is a self-check only.
Retain the stated data, units, signs and precision. Numerical agreement is a self-check only.
Retain the stated data, units, signs and precision. Numerical agreement is a self-check only.
Retain the stated data, units, signs and precision. Numerical agreement is a self-check only.
Retain the stated data, units, signs and precision. Numerical agreement is a self-check only.
Retain the stated data, units, signs and precision. Numerical agreement is a self-check only.
Retain the stated data, units, signs and precision. Numerical agreement is a self-check only.
A written attempt needs actual reasoning; text presence does not approve the argument.
A written attempt needs actual reasoning; text presence does not approve the argument.
These are original fixed cases for self-checking, not automatic marking, mastery or teacher/specialist/formal-assessment approval. The stated median-of-halves convention is a chosen convention. Grouped midpoint means and within-class CF readings remain estimates; a plateau can give a full interval. A physical instrument and calibrated graph are separate from the screen. No probability credit follows.
Use two fractions of the actual total
For a complete cumulative-frequency graph, find the final total N first. Estimate Q1 at cumulative height N/4 and Q3 at height 3N/4. Each height needs a horizontal guide to the curve and a vertical guide to the measurement axis. The quartiles are measured values; the heights used to find them are cumulative counts.
The interquartile range is the upper value reading minus the lower value reading. A wide class interval can place the two intersections far apart even when their count heights are familiar fractions. Do not confuse class width, frequency density or total frequency with a quartile value; these belong to different descriptions of the data.
Subtract readings before final rounding
Use the graph’s calibration and retain reasonable precision in each read-off until you calculate their difference. Rounding both quartiles prematurely can change the final IQR. The original grouped observations are not available, so a precise proportional calculation on a supplied straight guide still supports an estimate of the data’s IQR rather than an exact recovery of it.
A horizontal plateau at a quartile height gives an interval of possible graph-level quartile readings. If Q1 can lie between a and b while Q3 has the single reading c, then the IQR can lie between c − b and c − a. Preserve that interval and explain the missing choice; do not invent a numerical quartile solely to make subtraction convenient.
Compare distributions on their own scales
When two cumulative graphs have different totals, their quartile heights differ too. Take a quarter and three quarters of each graph’s own N. Equal raw cumulative heights would generally represent different proportions of those two populations, so comparing at one common count can misidentify their medians or quartiles.
Compare the resulting median and IQR in the same measurement units and with a purpose that supports the conclusion. A smaller IQR suggests a narrower central spread, while a different median describes a different typical level. Equal model medians and IQRs do not prove the underlying data sets identical or establish a formal statistical test; explain only what the supplied readings support.
Sources for this lesson
- Pearson Mathematics A linear specification · Issue 2 · Foundation printed24/physical30; Higher printed39/physical45; inheritance printed27/physical33
- Pearson 2026/2027 entry manual · centre regions physical3; Mathematics A physical25
- Pearson second-edition modular book/Hub map · literal navigation only · physical9,10,11
Pause and explain
Unrounded quartile readings are 9.8 cm and 24.6 cm. What IQR should be calculated before any further requested rounding?
Worked example
From the supplied CF guide through (0,0), (10,8), (20,24), (30,36), (40,40), draw quartile read-offs and estimate the IQR to 1 decimal place. Keep unrounded readings until subtraction. On the supplied calibrated diagram, show each requested horizontal and vertical read-off guide; keep the measurement unit and any complete overlap interval.
Show the worked solution
- Check the supplied axis labels and tick intervals. Read the completed cumulative total for each panel. Draw a horizontal guide at each requested fraction of its total, then a vertical guide from the actual intersection to the measurement axis; if a height overlaps a plateau, show both ends of the overlap.
- The total is 40, so use cumulative heights 10 and 30, not the horizontal positions 10 and 30 by assumption.
- The straight-guide model gives Q1 = 10 + 2/16 × 10 = 11.25 minutes and Q3 = 20 + 6/12 × 10 = 25 minutes.
- IQR = 25 − 11.25 = 13.75 minutes, giving a graph-based estimate about 13.8 minutes. Subtract before rounding.
Answer Use N = 40, Q1 height 10 and Q3 height 30. The straight-guide value readings are 11.25 and 25 minutes. Their model difference is 13.75 minutes; report the graph-based IQR estimate as about 13.8 minutes.
Try a topic test
Choose Easy, Normal or Difficult. Save your answers and open worked review after finishing.
Test this topic →From guided practice to a new situation
Write your answer and reasoning first. Use a hint only if you are stuck. The model solution is for self-checking; your written work is not automatically marked.
A supplied CF straight guide has points (0,0), (5,5), (10,15), (20,35), (30,40), for mass in kg. Estimate Q1, Q3 and IQR using drawn guides. Explain why unequal horizontal class widths do not change the cumulative heights used. On the supplied calibrated diagram, show each requested horizontal and vertical read-off guide; keep the measurement unit and any complete overlap interval.
Give me a hint
Use the total to find both quartile heights, then subtract the value readings rather than their count heights.
Compare my reasoning
- Check the supplied axis labels and tick intervals. Read the completed cumulative total for each panel. Draw a horizontal guide at each requested fraction of its total, then a vertical guide from the actual intersection to the measurement axis; if a height overlaps a plateau, show both ends of the overlap.
- There are 40 observations, so quartile heights are 10 and 30 regardless of the horizontal class widths.
- At height 10 the guide gives Q1 = 7.5 kg; at height 30 it gives Q3 = 17.5 kg.
- IQR is about 10.0 kg. Unequal widths affect where the intersections lie, not the fractions N/4 and 3N/4.
Use N = 40, Q1 height 10 and Q3 height 30. The straight-guide value readings are 7.5 and 17.5 kg. Their model difference is 10 kg; report the graph-based IQR estimate as about 10.0 kg.
Look for these in your work
- Find ranks from the total.
- Read each value using its own segment.
- State IQR in kg, not observations.
Two supplied CF guides, in minutes, are A: (0,0),(10,5),(20,25),(30,35),(40,40) and B: (0,0),(10,10),(20,50),(30,70),(40,80). Estimate each median and IQR with drawn guides. Can B be called more spread out merely because its cumulative counts are larger? On the supplied calibrated diagram, show each requested horizontal and vertical read-off guide; keep the measurement unit and any complete overlap interval.
Give me a hint
Find each graph’s own total before drawing its median and quartile guides.
Compare my reasoning
- Check the supplied axis labels and tick intervals. Read the completed cumulative total for each panel. Draw a horizontal guide at each requested fraction of its total, then a vertical guide from the actual intersection to the measurement axis; if a height overlaps a plateau, show both ends of the overlap.
- For A use cumulative heights 10, 20, 30; for B use 20, 40, 60. The totals are different.
- For both straight-guide distributions, Q1 = 12.5, median = 17.5 and Q3 = 25 minutes. Their IQRs are both 12.5 minutes.
- B doubles every cumulative count. That changes sample size, not the relative distribution in this model, so the larger cumulative heights alone do not establish larger spread.
A has N = 40 and B has N = 80, so use their own median/quartile heights. Both straight-guide distributions give estimated median 17.5 minutes, Q1 12.5 minutes, Q3 25 minutes and IQR 12.5 minutes. B’s larger cumulative counts reflect twice the sample size, not a larger model IQR.
Look for these in your work
- Use a separate N for each graph.
- Construct all requested read-offs.
- Compare measures in minutes rather than absolute cumulative counts.
A CF straight guide is supplied through (0,0), (10,10), (20,10), (30,30), (40,40). Draw the Q1 and Q3 height guides. State all possible graph-level Q1 readings and the corresponding IQR interval. Explain why reporting one exact IQR would add an assumption. On the supplied calibrated diagram, show each requested horizontal and vertical read-off guide; keep the measurement unit and any complete overlap interval.
Give me a hint
Keep the entire Q1 interval and subtract its endpoints from the Q3 reading in the correct order.
Compare my reasoning
- Check the supplied axis labels and tick intervals. Read the completed cumulative total for each panel. Draw a horizontal guide at each requested fraction of its total, then a vertical guide from the actual intersection to the measurement axis; if a height overlaps a plateau, show both ends of the overlap.
- The total is 40, giving quartile heights 10 and 30. At height 10, the supplied guide overlaps every x from 10 to 20 cm.
- Q3 is read at x = 30 cm. Therefore 30 − Q1 varies from 10 to 20 cm; retain the full IQR interval [10,20] cm.
- No unique Q1 or IQR follows from this plateau guide alone. A chosen endpoint or midpoint would require an additional convention, and the individual data are still not known.
Use cumulative heights 10 and 30. The Q1 graph-level readings form [10,20] cm and Q3 is read at 30 cm; the corresponding IQR readings form [10,20] cm. No unique IQR follows without an extra rule.
Look for these in your work
- Retain the complete quartile overlap.
- Subtract interval endpoints in the correct order.
- Explain nonuniqueness without inventing observations.
Common mistakes
- Using the same cumulative quartile heights for graphs with different totals.
- Subtracting cumulative counts instead of the quartile values read on the measurement axis.
- Rounding too early or forcing one IQR when a quartile plateau leaves an interval.
What can you explain now?
Why should two graphs with different sample totals use different cumulative heights for their quartile read-offs?
Compare with the explanation
Quartiles represent fractions of each graph’s own population, so the count heights are based on that graph’s N.
A common raw count can represent a quarter of one population and a different fraction of another. Compare the value readings obtained at corresponding proportions.
After trying it yourself, choose your next review. This is your self-assessment.
Your review choice appears on Today. Sign in to sync it across devices.
Make it stick
Explain how to find two quartiles, form an estimated IQR, compare different sample totals and retain uncertainty from a horizontal plateau.
If you needed the solution, close it and solve the problem again from a blank page. A correct answer is stronger when you can explain the reason for each step.